Articles | Volume 9, issue 9
https://doi.org/10.5194/gmd-9-2909-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-2909-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
31 Aug 2016
Model description paper |
| 31 Aug 2016
DebrisInterMixing-2.3: a finite volume solver for three-dimensional debris-flow simulations with two calibration parameters – Part 1: Model description
Albrecht von Boetticher
CORRESPONDING AUTHOR
Department of Environmental Systems Science,
ETH Zentrum, CHN H41, 8092 Zürich, Switzerland
Swiss Federal Research Institute WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Jens M. Turowski
Helmholtz-Centre Potsdam GFZ
German Research Center for Geosciences,
Telegrafenberg, 14473 Potsdam, Germany
Brian W. McArdell
Swiss Federal Research Institute WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Dieter Rickenmann
Swiss Federal Research Institute WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
James W. Kirchner
Department of Environmental Systems Science,
ETH Zentrum, CHN H41, 8092 Zürich, Switzerland
Swiss Federal Research Institute WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
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Nikos Theodoratos and James W. Kirchner
Earth Surf. Dynam., 9, 1545–1561, https://doi.org/10.5194/esurf-9-1545-2021, https://doi.org/10.5194/esurf-9-1545-2021, 2021
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Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar
Hydrol. Earth Syst. Sci., 25, 5937–5950, https://doi.org/10.5194/hess-25-5937-2021, https://doi.org/10.5194/hess-25-5937-2021, 2021
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Jacob Hirschberg, Alexandre Badoux, Brian W. McArdell, Elena Leonarduzzi, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 21, 2773–2789, https://doi.org/10.5194/nhess-21-2773-2021, https://doi.org/10.5194/nhess-21-2773-2021, 2021
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Odin Marc, Jens M. Turowski, and Patrick Meunier
Earth Surf. Dynam., 9, 995–1011, https://doi.org/10.5194/esurf-9-995-2021, https://doi.org/10.5194/esurf-9-995-2021, 2021
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Scott T. Allen and James W. Kirchner
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-683, https://doi.org/10.5194/hess-2020-683, 2021
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Georgios Maniatis, Trevor Hoey, Rebecca Hodge, Dieter Rickenmann, and Alexandre Badoux
Earth Surf. Dynam., 8, 1067–1099, https://doi.org/10.5194/esurf-8-1067-2020, https://doi.org/10.5194/esurf-8-1067-2020, 2020
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Jana von Freyberg, Julia L. A. Knapp, Andrea Rücker, Bjørn Studer, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 5821–5834, https://doi.org/10.5194/hess-24-5821-2020, https://doi.org/10.5194/hess-24-5821-2020, 2020
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Joost Buitink, Lieke A. Melsen, James W. Kirchner, and Adriaan J. Teuling
Geosci. Model Dev., 13, 6093–6110, https://doi.org/10.5194/gmd-13-6093-2020, https://doi.org/10.5194/gmd-13-6093-2020, 2020
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James W. Kirchner and Julia L. A. Knapp
Hydrol. Earth Syst. Sci., 24, 5539–5558, https://doi.org/10.5194/hess-24-5539-2020, https://doi.org/10.5194/hess-24-5539-2020, 2020
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Marius G. Floriancic, Wouter R. Berghuijs, Tobias Jonas, James W. Kirchner, and Peter Molnar
Hydrol. Earth Syst. Sci., 24, 5423–5438, https://doi.org/10.5194/hess-24-5423-2020, https://doi.org/10.5194/hess-24-5423-2020, 2020
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James W. Kirchner, Sarah E. Godsey, Madeline Solomon, Randall Osterhuber, Joseph R. McConnell, and Daniele Penna
Hydrol. Earth Syst. Sci., 24, 5095–5123, https://doi.org/10.5194/hess-24-5095-2020, https://doi.org/10.5194/hess-24-5095-2020, 2020
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Streams and groundwaters often show daily cycles in response to snowmelt and evapotranspiration. These typically have a roughly 6 h time lag, which is often interpreted as a travel-time lag. Here we show that it is instead primarily a phase lag that arises because aquifers integrate their inputs over time. We further show how these cycles shift seasonally, mirroring the springtime retreat of snow cover to higher elevations and the seasonal advance and retreat of photosynthetic activity.
Elham Rouholahnejad Freund, Massimiliano Zappa, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 5015–5025, https://doi.org/10.5194/hess-24-5015-2020, https://doi.org/10.5194/hess-24-5015-2020, 2020
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Evapotranspiration (ET) is the largest flux from the land to the atmosphere and thus contributes to Earth's energy and water balance. Due to its impact on atmospheric dynamics, ET is a key driver of droughts and heatwaves. In this paper, we demonstrate how averaging over land surface heterogeneity contributes to substantial overestimates of ET fluxes. We also demonstrate how one can correct for the effects of small-scale heterogeneity without explicitly representing it in land surface models.
Tjalling de Haas, Wiebe Nijland, Brian W. McArdell, and Maurice W. M. L. Kalthof
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2020-43, https://doi.org/10.5194/esurf-2020-43, 2020
Preprint withdrawn
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High-quality digital surface models generated by automated photogrammetry techniques on aerial images captured with drones are increasingly used for topographic change detection. We demonstrate that co-aligning the images from multiple surveys strongly enhances the accuracy of topographic change detection. We find that co-alignment leads to particularly large improvements in the accuracy of poorly aligned surveys that have severe offsets when processed individually.
Nikos Theodoratos and James W. Kirchner
Earth Surf. Dynam., 8, 505–526, https://doi.org/10.5194/esurf-8-505-2020, https://doi.org/10.5194/esurf-8-505-2020, 2020
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We non-dimensionalized a commonly used model of landscape evolution that includes an incision threshold. Whereas the original model included four parameters, we obtained a dimensionless form with a single parameter, which quantifies the relative importance of the incision threshold. Working with this form saves computational time and simplifies theoretical analyses.
Julia L. A. Knapp, Jana von Freyberg, Bjørn Studer, Leonie Kiewiet, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 2561–2576, https://doi.org/10.5194/hess-24-2561-2020, https://doi.org/10.5194/hess-24-2561-2020, 2020
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Changes of stream water chemistry in response to discharge changes provide important insights into the storage and release of water from the catchment. Here we investigate the variability in concentration–discharge relationships among different solutes and hydrologic events and relate it to catchment conditions and dominant water sources.
Elham Rouholahnejad Freund, Ying Fan, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 1927–1938, https://doi.org/10.5194/hess-24-1927-2020, https://doi.org/10.5194/hess-24-1927-2020, 2020
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Francesc Gallart, Jana von Freyberg, María Valiente, James W. Kirchner, Pilar Llorens, and Jérôme Latron
Hydrol. Earth Syst. Sci., 24, 1101–1107, https://doi.org/10.5194/hess-24-1101-2020, https://doi.org/10.5194/hess-24-1101-2020, 2020
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Jens Martin Turowski
Earth Surf. Dynam., 8, 103–122, https://doi.org/10.5194/esurf-8-103-2020, https://doi.org/10.5194/esurf-8-103-2020, 2020
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Bedrock channels are the conveyor belts of mountain regions, evacuating sediment produced by erosion. Bedrock channel morphology and dynamics affect sediment transport rates and local erosion and set the base level for hillslope response. Here, using mechanistic considerations of the processes of fluvial erosion and transport, and considerations of the mass balance of sediment and bedrock, I discuss the principles governing steady-state channel morphology and the dynamic paths to achieve it.
James W. Kirchner and Scott T. Allen
Hydrol. Earth Syst. Sci., 24, 17–39, https://doi.org/10.5194/hess-24-17-2020, https://doi.org/10.5194/hess-24-17-2020, 2020
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Perhaps the oldest question in hydrology is
Where does water go when it rains?. Here we present a new way to measure how the terrestrial water cycle partitions precipitation into its two ultimate fates:
green waterthat is evaporated or transpired back to the atmosphere and
blue waterthat is discharged to stream channels. Our analysis may help in gauging the vulnerability of both water resources and terrestrial ecosystems to changes in rainfall patterns.
H. J. Ilja van Meerveld, James W. Kirchner, Marc J. P. Vis, Rick S. Assendelft, and Jan Seibert
Hydrol. Earth Syst. Sci., 23, 4825–4834, https://doi.org/10.5194/hess-23-4825-2019, https://doi.org/10.5194/hess-23-4825-2019, 2019
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Flowing stream networks extend and retract seasonally and in response to precipitation. This affects the distances and thus the time that it takes a water molecule to reach the flowing stream and the stream outlet. When the network is fully extended, the travel times are short, but when the network retracts, the travel times become longer and more uniform. These dynamics should be included when modeling solute or pollutant transport.
Julia L. A. Knapp, Colin Neal, Alessandro Schlumpf, Margaret Neal, and James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 4367–4388, https://doi.org/10.5194/hess-23-4367-2019, https://doi.org/10.5194/hess-23-4367-2019, 2019
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We describe, present, and make publicly available two extensive data sets of stable water isotopes in streamwater and precipitation at Plynlimon, Wales, consisting of measurements at 7-hourly intervals for 17 months and at weekly intervals for 4.25 years. We use these data to calculate new water fractions and transit time distributions for different discharge rates and seasons, thus quantifying the contribution of recent precipitation to streamflow under different conditions.
Mitch K. D'Arcy, Taylor F. Schildgen, Jens M. Turowski, and Pedro DiNezio
Earth Surf. Dynam., 7, 755–771, https://doi.org/10.5194/esurf-7-755-2019, https://doi.org/10.5194/esurf-7-755-2019, 2019
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The age of formation of sedimentary deposits is often interpreted to record information about past environmental changes. Here, we show that the timing of abandonment of surfaces also provides valuable information. We derive a new set of equations that can be used to estimate when a sedimentary surface was abandoned based on what is known about its activity from surface dating. Estimates of abandonment age can benefit a variety of geomorphic analyses, which we illustrate with a case study.
Scott T. Allen, Scott Jasechko, Wouter R. Berghuijs, Jeffrey M. Welker, Gregory R. Goldsmith, and James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 3423–3436, https://doi.org/10.5194/hess-23-3423-2019, https://doi.org/10.5194/hess-23-3423-2019, 2019
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We developed global maps that concisely quantify the seasonality of stable isotope ratios in precipitation, using data from 653 meteorological stations across all seven continents. We make these gridded global maps publicly available to support diverse stable isotope applications.
Andrea Rücker, Stefan Boss, James W. Kirchner, and Jana von Freyberg
Hydrol. Earth Syst. Sci., 23, 2983–3005, https://doi.org/10.5194/hess-23-2983-2019, https://doi.org/10.5194/hess-23-2983-2019, 2019
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To better understand how rain-on-snow (ROS) events affect snowpack outflow volumes and streamflow generation, we measured snowpack outflow volumes and isotopic composition during 10 ROS events with automated snowmelt lysimeters at three locations in a pre-Alpine catchment. We quantified the spatio-temporal variability of snowpack outflow and its relative contribution to streamflow, and identified rainfall characteristics and initial snow depth as major controls on snow hydrological processes.
Scott T. Allen, James W. Kirchner, Sabine Braun, Rolf T. W. Siegwolf, and Gregory R. Goldsmith
Hydrol. Earth Syst. Sci., 23, 1199–1210, https://doi.org/10.5194/hess-23-1199-2019, https://doi.org/10.5194/hess-23-1199-2019, 2019
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We used stable isotopes of xylem water to study differences in the seasonal origin of water in more than 900 individual trees from three dominant species in 182 Swiss forested sites. We discovered that midsummer transpiration was mostly supplied by winter precipitation across diverse humid climates. Our findings provide new insights into tree vulnerability to droughts, transport of water (and thus solutes) in soils, and the climatic information conveyed by plant-tissue isotopes.
Odin Marc, Robert Behling, Christoff Andermann, Jens M. Turowski, Luc Illien, Sigrid Roessner, and Niels Hovius
Earth Surf. Dynam., 7, 107–128, https://doi.org/10.5194/esurf-7-107-2019, https://doi.org/10.5194/esurf-7-107-2019, 2019
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We mapped eight monsoon-related (> 100 m2) and large (> 0.1 km2) landslides in the Nepal Himalayas since 1970. Adding inventories of Holocene landslides, giant landslides (> 1 km3), and landslides from the 2015 Gorkha earthquake, we constrain the size–frequency distribution of monsoon- and earthquake-induced landslides. Both contribute ~50 % to a long-term (> 10 kyr) total erosion of ~2 mm yr-1, matching the long-term exhumation rate. Large landslides rarer than 10Be sampling time drive erosion.
James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 303–349, https://doi.org/10.5194/hess-23-303-2019, https://doi.org/10.5194/hess-23-303-2019, 2019
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How long does it take for raindrops to become streamflow? Here I propose a new approach to this old problem. I show how we can use time series of isotope data to measure the average fraction of same-day rainfall appearing in streamflow, even if this fraction varies greatly from rainstorm to rainstorm. I show that we can quantify how this fraction changes from small rainstorms to big ones, and from high flows to low flows, and how it changes with the lag time between rainfall and streamflow.
Virginia Ruiz-Villanueva, Alexandre Badoux, Dieter Rickenmann, Martin Böckli, Salome Schläfli, Nicolas Steeb, Markus Stoffel, and Christian Rickli
Earth Surf. Dynam., 6, 1115–1137, https://doi.org/10.5194/esurf-6-1115-2018, https://doi.org/10.5194/esurf-6-1115-2018, 2018
Jana von Freyberg, Bjørn Studer, Michael Rinderer, and James W. Kirchner
Hydrol. Earth Syst. Sci., 22, 5847–5865, https://doi.org/10.5194/hess-22-5847-2018, https://doi.org/10.5194/hess-22-5847-2018, 2018
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We show event- and pre-event-water volumes as fractions of precipitation, rather than discharge, to provide an alternative and more insightful approach to study catchment hydrological processes. For this, we analyze 24 storm events using high-frequency measurements of stable water isotopes in stream water and precipitation at a pre-Alpine catchment. Antecedent wetness and storm characteristics are dominant controls on event-water discharge and pre-event-water mobilization from storage.
Daniele Penna, Luisa Hopp, Francesca Scandellari, Scott T. Allen, Paolo Benettin, Matthias Beyer, Josie Geris, Julian Klaus, John D. Marshall, Luitgard Schwendenmann, Till H. M. Volkmann, Jana von Freyberg, Anam Amin, Natalie Ceperley, Michael Engel, Jay Frentress, Yamuna Giambastiani, Jeff J. McDonnell, Giulia Zuecco, Pilar Llorens, Rolf T. W. Siegwolf, Todd E. Dawson, and James W. Kirchner
Biogeosciences, 15, 6399–6415, https://doi.org/10.5194/bg-15-6399-2018, https://doi.org/10.5194/bg-15-6399-2018, 2018
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Understanding how water flows through ecosystems is needed to provide society and policymakers with the scientific background to manage water resources sustainably. Stable isotopes of hydrogen and oxygen in water are a powerful tool for tracking water fluxes, although the heterogeneity of natural systems and practical methodological issues still limit their full application. Here, we examine the challenges in this research field and highlight new perspectives based on interdisciplinary research.
Nikos Theodoratos, Hansjörg Seybold, and James W. Kirchner
Earth Surf. Dynam., 6, 779–808, https://doi.org/10.5194/esurf-6-779-2018, https://doi.org/10.5194/esurf-6-779-2018, 2018
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We perform dimensional analysis on a frequently used landscape evolution model (LEM). Defining characteristic scales in a novel way, we significantly simplify the LEM and develop an efficient numerical modeling approach. Our characteristic scales are physically meaningful; they quantify competitions between landscape-forming processes and are related to salient properties of landscape topography. Dimensional analyses of other LEMs may benefit from our approach in defining characteristic scales.
Jana von Freyberg, Scott T. Allen, Stefan Seeger, Markus Weiler, and James W. Kirchner
Hydrol. Earth Syst. Sci., 22, 3841–3861, https://doi.org/10.5194/hess-22-3841-2018, https://doi.org/10.5194/hess-22-3841-2018, 2018
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We explored how the fraction of streamflow younger than ca. 3 months (Fyw) varies with landscape characteristics and climatic forcing, using an extensive isotope data set from 22 Swiss catchments. Overall, Fyw tends to be larger when catchments are wet and discharge is correspondingly higher, indicating an increase in the proportional contribution of faster flow paths at higher flows. We quantify this
discharge sensitivityof Fyw and relate it to the dominant streamflow-generating mechanisms.
Anne Schöpa, Wei-An Chao, Bradley P. Lipovsky, Niels Hovius, Robert S. White, Robert G. Green, and Jens M. Turowski
Earth Surf. Dynam., 6, 467–485, https://doi.org/10.5194/esurf-6-467-2018, https://doi.org/10.5194/esurf-6-467-2018, 2018
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On 21 July 2014, a voluminous landslide entered the caldera lake at Askja, Iceland, and created tsunami waves inundating famous tourist spots. The high hazard potential of the site motivated our study in which we analysed seismic data and found a precursory tremor signal intensifying in the 30 min before the landslide. Our paper shows the potential of seismic monitoring techniques to detect precursory activity before a big landslide that could be used for an early-warning system.
Paolo Benettin, Till H. M. Volkmann, Jana von Freyberg, Jay Frentress, Daniele Penna, Todd E. Dawson, and James W. Kirchner
Hydrol. Earth Syst. Sci., 22, 2881–2890, https://doi.org/10.5194/hess-22-2881-2018, https://doi.org/10.5194/hess-22-2881-2018, 2018
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Evaporation causes the isotopic composition of soil water to become different from that of the original precipitation source. If multiple samples originating from the same source are available, they can be used to reconstruct the original source composition. However, soil water is influenced by seasonal variability in both precipitation sources and evaporation patterns. We show that this variability, if not accounted for, can lead to biased estimates of the precipitation source water.
Jens Martin Turowski
Earth Surf. Dynam., 6, 29–48, https://doi.org/10.5194/esurf-6-29-2018, https://doi.org/10.5194/esurf-6-29-2018, 2018
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Bedrock channels are a key component of mountainous landscapes. Here, a new model of the steady-state morphology, including channel width, slope and sinuosity, is derived from process physics considerations. The model compares favourably to observed scaling relations.
Michael Dietze, Jens M. Turowski, Kristen L. Cook, and Niels Hovius
Earth Surf. Dynam., 5, 757–779, https://doi.org/10.5194/esurf-5-757-2017, https://doi.org/10.5194/esurf-5-757-2017, 2017
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Rockfall is an essential geomorphic process and a hazard in steep landscapes which is hard to constrain with traditional approaches. Seismic methods allow for the detection, location, characterisation and linking of events to triggers by lag times. This new technique reveals 49 rockfalls in 6 months with seasonally varying locations. Freeze–thaw action accounts for only 5 events, whereas 19 rockfalls were caused by rain with a 1 h peak lag time, and 17 events were due to diurnal thermal forcing.
Albrecht von Boetticher, Jens M. Turowski, Brian W. McArdell, Dieter Rickenmann, Marcel Hürlimann, Christian Scheidl, and James W. Kirchner
Geosci. Model Dev., 10, 3963–3978, https://doi.org/10.5194/gmd-10-3963-2017, https://doi.org/10.5194/gmd-10-3963-2017, 2017
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The open-source fluid dynamic solver presented in v. Boetticher et al. (2016) combines a Coulomb viscosplastic rheological model with a Herschel–Bulkley model based on material properties for 3-D debris flow simulations. Here, we validate the solver and illustrate the model sensitivity to water content, channel curvature, content of fine material and channel bed roughness. We simulate both laboratory-scale and large-scale debris-flow experiments, using only one of the two calibration parameters.
Dieter Rickenmann and Bruno Fritschi
Earth Surf. Dynam., 5, 669–687, https://doi.org/10.5194/esurf-5-669-2017, https://doi.org/10.5194/esurf-5-669-2017, 2017
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The Swiss plate geophone system is a bedload surrogate measuring technique. Calibration measurements for this technique were performed in two mountain streams in Austria, using geophone impulse rates (a summary value) and directly measured bedload transport rates. Implausible geophone impulse counts are discussed that were recorded during periods with smaller discharges without any bedload transport, and that are likely caused by vehicle movement very near to the measuring sites.
Michael Dietze, Solmaz Mohadjer, Jens M. Turowski, Todd A. Ehlers, and Niels Hovius
Earth Surf. Dynam., 5, 653–668, https://doi.org/10.5194/esurf-5-653-2017, https://doi.org/10.5194/esurf-5-653-2017, 2017
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We use a seismometer network to detect and locate rockfalls, a key process shaping steep mountain landscapes. When tested against laser scan surveys, all seismically detected events could be located with an average deviation of 81 m. Seismic monitoring provides insight to the dynamics of individual rockfalls, which can be as small as 0.0053 m3. Thus, seismic methods provide unprecedented temporal, spatial and kinematic details about this important process.
Antonius Golly and Jens M. Turowski
Earth Surf. Dynam., 5, 557–570, https://doi.org/10.5194/esurf-5-557-2017, https://doi.org/10.5194/esurf-5-557-2017, 2017
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Researchers of fluvial geomorphology require reliable information on channel width and its change in space and time. For example, to study bank erosion rates we need the local position of channel banks before and after a high flood event. Although deriving these metrics seems simple, researchers often use manual or arbitrary approaches that are not objective and reproducible. Here, we present an open-source software tool
cmgo(R package) that meets the requirements of academic research.
Fabian Walter, Arnaud Burtin, Brian W. McArdell, Niels Hovius, Bianca Weder, and Jens M. Turowski
Nat. Hazards Earth Syst. Sci., 17, 939–955, https://doi.org/10.5194/nhess-17-939-2017, https://doi.org/10.5194/nhess-17-939-2017, 2017
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Debris flows are naturally occuring mass motion events, which mobilize loose material in steep Alpine torrents. The destructive potential of debris flows is well known and demands early warning. Here we apply the amplitude source location (ASL) method to seismic ground vibrations induced by a debris flow event in Switzerland. The method efficiently detects the initiation of the event and traces its front propagation down the torrent channel.
Jens M. Turowski and Rebecca Hodge
Earth Surf. Dynam., 5, 311–330, https://doi.org/10.5194/esurf-5-311-2017, https://doi.org/10.5194/esurf-5-311-2017, 2017
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Bedrock incision by rivers is driven by the impacts of sediment particles moved by the water flow. Sediment residing on the bed can protect the rock from impacts, thereby reducing erosion rates, a phenomenon known as the cover effect. The cover effect has been shown to be important in many field and laboratory experiments. Here, we develop a mathematical framework to describe the cover effect which can be used to compare data and to predict the extent of cover in streams.
Florian Frank, Brian W. McArdell, Nicole Oggier, Patrick Baer, Marc Christen, and Andreas Vieli
Nat. Hazards Earth Syst. Sci., 17, 801–815, https://doi.org/10.5194/nhess-17-801-2017, https://doi.org/10.5194/nhess-17-801-2017, 2017
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This study describes a sensitivity analysis of the RAMMS debris-flow entrainment model, which is intended to help solve problems related to predicting the runout of debris flows. The results indicate that the entrainment model predicts plausible erosion volumes in comparison with field data. These eroded volumes are sensitive to the initial landslide volume, suggesting that this tool may be useful for both reconstruction of historical events and modeling of debris flow scenarios.
Jana von Freyberg, Bjørn Studer, and James W. Kirchner
Hydrol. Earth Syst. Sci., 21, 1721–1739, https://doi.org/10.5194/hess-21-1721-2017, https://doi.org/10.5194/hess-21-1721-2017, 2017
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We present a newly developed instrument package that enables the online analysis of stable water isotopes and major ion chemistry at 30 min intervals in the field. The resulting data streams provide an unprecedented view of hydrochemical dynamics on the catchment scale. Based on a detailed analysis of the variable behavior of isotopic and chemical tracers in stream water and precipitation over a 4-week period, we developed a conceptual hypothesis for runoff generation in the studied catchment.
Dieter Rickenmann, Gilles Antoniazza, Carlos R. Wyss, Bruno Fritschi, and Stefan Boss
Proc. IAHS, 375, 5–10, https://doi.org/10.5194/piahs-375-5-2017, https://doi.org/10.5194/piahs-375-5-2017, 2017
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Bedload transport measurements were performed with acoustic sensors (geophones and accelerometers) mounted underneath impact plates during summer 2015 in the Albula River in Switzerland. The measurements showed that the signal response in terms of geophone and accelerometer impulses is comparable for both types of sensors and that there is a good correlation between discharge data and impulses recorded by both types of sensors.
Elham Rouholahnejad Freund and James W. Kirchner
Hydrol. Earth Syst. Sci., 21, 217–233, https://doi.org/10.5194/hess-21-217-2017, https://doi.org/10.5194/hess-21-217-2017, 2017
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Our analysis shows that averaging over sub-grid heterogeneity in precipitation and potential evapotranspiration (ET), as typical earth system models do, overestimates the average of the spatially variable ET. We also show when aridity index increases with altitude, lateral redistribution would transfer water from more humid uplands to more arid lowlands, resulting in a net increase in ET. Therefore, the Earth system models that neglect lateral transfer underestimate ET in those regions.
Alexander R. Beer, James W. Kirchner, and Jens M. Turowski
Earth Surf. Dynam., 4, 885–894, https://doi.org/10.5194/esurf-4-885-2016, https://doi.org/10.5194/esurf-4-885-2016, 2016
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Spatial bedrock erosion data from stream channels are important for engineering issues and landscape evolution model assessment. However, acquiring such data is challenging and only few data sets exist. Detecting changes in repeated photographs of painted bedrock surfaces easily allows for semi-quantitative conclusions on the spatial distribution of sediment transport and its effects: abrasion on surfaces facing the streamflow and shielding of surfaces by abundant sediment.
Arnaud Burtin, Niels Hovius, and Jens M. Turowski
Earth Surf. Dynam., 4, 285–307, https://doi.org/10.5194/esurf-4-285-2016, https://doi.org/10.5194/esurf-4-285-2016, 2016
J. W. Kirchner
Hydrol. Earth Syst. Sci., 20, 279–297, https://doi.org/10.5194/hess-20-279-2016, https://doi.org/10.5194/hess-20-279-2016, 2016
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Catchment mean transit times have been widely inferred from seasonal cycles of environmental tracers in precipitation and streamflow. Here I show that these cycles yield strongly biased estimates of mean transit times in spatially heterogeneous catchments (and, by implication, in real-world catchments). However, I also show that these cycles can be used to reliably estimate the fraction of "young" water in streamflow, meaning water that fell as precipitation less than roughly 2–3 months ago.
J. W. Kirchner
Hydrol. Earth Syst. Sci., 20, 299–328, https://doi.org/10.5194/hess-20-299-2016, https://doi.org/10.5194/hess-20-299-2016, 2016
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Here I show that seasonal tracer cycles yield strongly biased estimates of mean transit times in nonstationary catchments (and, by implication, in real-world catchments). However, they can be used to reliably estimate the fraction of "young" water in streamflow, meaning water that fell as precipitation less than roughly 2–3 months ago. This young water fraction varies systematically between high and low flows and may help in characterizing controls on stream chemistry.
F. Frank, B. W. McArdell, C. Huggel, and A. Vieli
Nat. Hazards Earth Syst. Sci., 15, 2569–2583, https://doi.org/10.5194/nhess-15-2569-2015, https://doi.org/10.5194/nhess-15-2569-2015, 2015
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The sudden onset of large and erosive debris flows has been observed recently in different catchments in Switzerland, implicating the importance of erosion for debris flow modelling. Therefore, an erosion model was established based on field data (relationship between maximum shear stress and erosion depth and rate) of several debris flows measured at the Illgraben. Erosion model tests at the Spreitgraben showed considerable improvements in runout pattern as well as hydrograph propagation.
F. Kobierska, T. Jonas, J. W. Kirchner, and S. M. Bernasconi
Hydrol. Earth Syst. Sci., 19, 3681–3693, https://doi.org/10.5194/hess-19-3681-2015, https://doi.org/10.5194/hess-19-3681-2015, 2015
A. von Boetticher, J. M. Turowski, B. W. McArdell, D. Rickenmann, M. Hürlimann, C. Scheidl, and J. W. Kirchner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-6379-2015, https://doi.org/10.5194/gmdd-8-6379-2015, 2015
Preprint withdrawn
M. Jochner, J. M. Turowski, A. Badoux, M. Stoffel, and C. Rickli
Earth Surf. Dynam., 3, 311–320, https://doi.org/10.5194/esurf-3-311-2015, https://doi.org/10.5194/esurf-3-311-2015, 2015
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The export of coarse particulate organic matter (CPOM) from mountain catchments seems to be strongly linked to rising discharge, but the mechanism leading to this is unclear. We show that log jams in a steep headwater stream are an effective barrier for CPOM export. Exceptional discharge events play a dual role: First, they destroy existing jams, releasing stored material. Second, they intensify channel--hillslope coupling, thereby recruiting logs to the channel, around which new jams can form.
A. R. Beer and J. M. Turowski
Earth Surf. Dynam., 3, 291–309, https://doi.org/10.5194/esurf-3-291-2015, https://doi.org/10.5194/esurf-3-291-2015, 2015
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We applied a spatiotemporally highly resolved dataset of discharge, sediment transport and bedrock erosion data to assess the validity of landscape evolution models at the process scale (resolution of square meters and minutes). The tools effect is found to be the dominant driver of erosion and an easy model is able to predict measured erosion. For larger scales common discharge-dependend modeling with a discharge threshold is adequate to regive the overal trend of the erosion signal.
K. Schraml, B. Thomschitz, B. W. McArdell, C. Graf, and R. Kaitna
Nat. Hazards Earth Syst. Sci., 15, 1483–1492, https://doi.org/10.5194/nhess-15-1483-2015, https://doi.org/10.5194/nhess-15-1483-2015, 2015
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In this paper we used two different numerical simulation models to replicate two debris-flow events in Austria and compare the range and sensitivity of the model input parameters. We expect that our results contribute to a better application of simulation models for hazard and risk assessment in alpine regions.
M. Stähli, M. Sättele, C. Huggel, B. W. McArdell, P. Lehmann, A. Van Herwijnen, A. Berne, M. Schleiss, A. Ferrari, A. Kos, D. Or, and S. M. Springman
Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, https://doi.org/10.5194/nhess-15-905-2015, 2015
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This review paper describes the state of the art in monitoring and predicting rapid mass movements for early warning. It further presents recent innovations in observation technologies and modelling to be used in future early warning systems (EWS). Finally, the paper proposes avenues towards successful implementation of next-generation EWS.
F. U. M. Heimann, D. Rickenmann, J. M. Turowski, and J. W. Kirchner
Earth Surf. Dynam., 3, 15–34, https://doi.org/10.5194/esurf-3-15-2015, https://doi.org/10.5194/esurf-3-15-2015, 2015
F. U. M. Heimann, D. Rickenmann, M. Böckli, A. Badoux, J. M. Turowski, and J. W. Kirchner
Earth Surf. Dynam., 3, 35–54, https://doi.org/10.5194/esurf-3-35-2015, https://doi.org/10.5194/esurf-3-35-2015, 2015
A. Burtin, N. Hovius, B. W. McArdell, J. M. Turowski, and J. Vergne
Earth Surf. Dynam., 2, 21–33, https://doi.org/10.5194/esurf-2-21-2014, https://doi.org/10.5194/esurf-2-21-2014, 2014
J. M. Turowski, A. Badoux, K. Bunte, C. Rickli, N. Federspiel, and M. Jochner
Earth Surf. Dynam., 1, 1–11, https://doi.org/10.5194/esurf-1-1-2013, https://doi.org/10.5194/esurf-1-1-2013, 2013
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mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
Selecting a conceptual hydrological model using Bayes' factors computed with Replica Exchange Hamiltonian Monte Carlo and Thermodynamic Integration
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Hannes Müller Schmied, Tim Trautmann, Sebastian Ackermann, Denise Cáceres, Martina Flörke, Helena Gerdener, Ellen Kynast, Thedini Asali Peiris, Leonie Schiebener, Maike Schumacher, and Petra Döll
Geosci. Model Dev., 17, 8817–8852, https://doi.org/10.5194/gmd-17-8817-2024, https://doi.org/10.5194/gmd-17-8817-2024, 2024
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Assessing water availability and water use at the global scale is challenging but essential for a range of purposes. We describe the newest version of the global hydrological model WaterGAP, which has been used for numerous water resource assessments since 1996. We show the effects of new model features, as well as model evaluations, against water abstraction statistics and observed streamflow and water storage anomalies. The publicly available model output for several variants is described.
João António Martins Careto, Rita Margarida Cardoso, Ana Russo, Daniela Catarina André Lima, and Pedro Miguel Matos Soares
Geosci. Model Dev., 17, 8115–8139, https://doi.org/10.5194/gmd-17-8115-2024, https://doi.org/10.5194/gmd-17-8115-2024, 2024
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This study proposes a new daily drought index, the generalised drought index (GDI). The GDI not only identifies the same events as established indices but is also capable of improving their results. The index is empirically based and easy to compute, not requiring fitting the data to a probability distribution. The GDI can detect flash droughts and longer-term events, making it a versatile tool for drought monitoring.
Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan
Geosci. Model Dev., 17, 7751–7766, https://doi.org/10.5194/gmd-17-7751-2024, https://doi.org/10.5194/gmd-17-7751-2024, 2024
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We develop an operational forecast system, Coastlines-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model has relatively low computational requirements, and results compare well with near-real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and wave predictions can improve in accuracy.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
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Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, https://doi.org/10.5194/gmd-17-7083-2024, 2024
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Geoscientists commonly use various potential evapotranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024, https://doi.org/10.5194/gmd-17-6949-2024, 2024
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The soil water potential (SWP) determines various soil water processes. Since remote sensing techniques cannot measure it directly, it is often deduced from volumetric water content (VWC) information. However, under dynamic field conditions, the relationship between SWP and VWC is highly ambiguous due to different factors that cannot be modeled with the classical approach. Applying a deep neural network with an autoencoder enables the prediction of the dynamic SWP.
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024, https://doi.org/10.5194/gmd-17-6819-2024, 2024
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Valid simulation results from global hydrological models (GHMs) are essential, e.g., to studying climate change impacts. Adapting GHMs to ungauged basins requires regionalization, enabling valid simulations. In this study, we highlight the impact of regionalization of GHMs on runoff simulations using an ensemble of regionalization methods for WaterGAP3. We have found that regionalization leads to temporally and spatially varying uncertainty, potentially reaching up to inter-model differences.
Zhi Li, Gregor Rickert, Na Zheng, Zhibo Zhang, Ilhan Özgen-Xian, and Daniel Caviedes-Voullième
EGUsphere, https://doi.org/10.5194/egusphere-2024-2588, https://doi.org/10.5194/egusphere-2024-2588, 2024
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We introduce SERGHEI-RE, a 3D subsurface flow simulator with performance-portable parallel computing capabilities. SERGHEI-RE performs effectively on various computational devices, from personal computers to advanced clusters. It allows users to solve flow equations with multiple numerical schemes, making it adaptable to various hydrological scenarios. Testing results show its accuracy and performance, confirming that SERGHEI-RE is a powerful tool for hydrological research.
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-106, https://doi.org/10.5194/gmd-2024-106, 2024
Revised manuscript accepted for GMD
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Multiple methods for measuring soil moisture beyond the point scale exist. Their validation generally hindered by lack of knowing the truth. We propose a virtual framework, in which this truth is fully known and the sensor observations for Cosmic Ray Neutron Sensing, Remote Sensing, and Hydrogravimetry are simulated. This allows the rigourous testing of these virtual sensors to understand their effectiveness and limitations.
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
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STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
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River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
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The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
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This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
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This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
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The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
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Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
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We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
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We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
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The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
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Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
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We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
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Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
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Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
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Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
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This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
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We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Damian N. Mingo, Remko Nijzink, Christophe Ley, and Jack S. Hale
EGUsphere, https://doi.org/10.5194/egusphere-2023-2865, https://doi.org/10.5194/egusphere-2023-2865, 2024
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Hydrologists are often faced with selecting amongst a set of competing models with different numbers of parameters and ability to fit available data. The Bayes’ factor is a tool that can be used to compare models, however it is very difficult to compute the Bayes’ factor numerically. In our paper we explore and develop highly efficient algorithms for computing the Bayes’ factor of hydrological systems, which will bring this useful tool for selecting models to everyday hydrological practice.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
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We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
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Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
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Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
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NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
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Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
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DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
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Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
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Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
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Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
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In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
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We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
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During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
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Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
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Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
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Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
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A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
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Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
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Short summary
Debris flows are characterized by unsteady flows of water with different content of clay, silt, sand, gravel, and large particles, resulting in a dense moving mixture mass. Here we present a three-dimensional fluid dynamic solver that simulates the flow as a mixture of a pressure-dependent rheology model of the gravel mixed with a Herschel–Bulkley rheology of the fine material suspension. We link rheological parameters to the material composition. The user must specify two free model parameters.
Debris flows are characterized by unsteady flows of water with different content of clay, silt,...
